{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "cfzQr7x-V4QI"
   },
   "source": [
    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/open-mmlab/mmediting/blob/master/demo/matting_tutorial.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "A9VoEGTL_R50"
   },
   "source": [
    "# MMEditing Tutorial-Matting\n",
    "\n",
    "Welcome to MMEditing! This is the official colab tutorial for using MMEditing for matting task. In this tutorial, you will learn to\n",
    "\n",
    "* perform inference with a MMEditing mattor,\n",
    "* train a new mattor with a new dataset.\n",
    "\n",
    "Let's start!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "-R6v39d__uJl"
   },
   "source": [
    "## Install MMEditing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch                         1.10.0+cu111\n",
      "torchaudio                    0.10.0+cu111\n",
      "torchsummary                  1.5.1\n",
      "torchtext                     0.11.0\n",
      "torchvision                   0.11.1+cu111\n"
     ]
    }
   ],
   "source": [
    "# Check PyTorch version\n",
    "!pip list | grep torch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting openmim\n",
      "  Downloading openmim-0.1.5.tar.gz (35 kB)\n",
      "Requirement already satisfied: Click==7.1.2 in /usr/local/lib/python3.7/dist-packages (from openmim) (7.1.2)\n",
      "Collecting colorama\n",
      "  Downloading colorama-0.4.4-py2.py3-none-any.whl (16 kB)\n",
      "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from openmim) (2.23.0)\n",
      "Collecting model-index\n",
      "  Downloading model_index-0.1.11-py3-none-any.whl (34 kB)\n",
      "Requirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from openmim) (1.3.5)\n",
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      "Collecting ordered-set\n",
      "  Downloading ordered_set-4.1.0-py3-none-any.whl (7.6 kB)\n",
      "Requirement already satisfied: markdown in /usr/local/lib/python3.7/dist-packages (from model-index->openmim) (3.3.6)\n",
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      "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->openmim) (2.10)\n",
      "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->openmim) (3.0.4)\n",
      "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->openmim) (1.24.3)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->openmim) (2021.10.8)\n",
      "Building wheels for collected packages: openmim\n",
      "  Building wheel for openmim (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
      "  Created wheel for openmim: filename=openmim-0.1.5-py2.py3-none-any.whl size=42503 sha256=73c8fbdde5bccccc5f7f988b130ae680165893e05d4f16d503bd79b64dd144d4\n",
      "  Stored in directory: /root/.cache/pip/wheels/16/8b/e1/bdebbbc687aa50224a5ce46fe97a040a0c59f92b34bfc750b6\n",
      "Successfully built openmim\n",
      "Installing collected packages: ordered-set, model-index, colorama, openmim\n",
      "Successfully installed colorama-0.4.4 model-index-0.1.11 openmim-0.1.5 ordered-set-4.1.0\n",
      "installing mmcv-full from wheel.\n",
      "Looking in links: https://download.openmmlab.com/mmcv/dist/cu111/torch1.10.0/index.html\n",
      "Collecting mmcv-full==1.4.6\n",
      "  Downloading https://download.openmmlab.com/mmcv/dist/cu111/torch1.10.0/mmcv_full-1.4.6-cp37-cp37m-manylinux1_x86_64.whl (46.0 MB)\n",
      "\u001b[K     |████████████████████████████████| 46.0 MB 9.3 MB/s \n",
      "\u001b[?25hRequirement already satisfied: Pillow in /usr/local/lib/python3.7/dist-packages (from mmcv-full==1.4.6) (7.1.2)\n",
      "Requirement already satisfied: pyyaml in /usr/local/lib/python3.7/dist-packages (from mmcv-full==1.4.6) (3.13)\n",
      "Requirement already satisfied: opencv-python>=3 in /usr/local/lib/python3.7/dist-packages (from mmcv-full==1.4.6) (4.1.2.30)\n",
      "Collecting yapf\n",
      "  Downloading yapf-0.32.0-py2.py3-none-any.whl (190 kB)\n",
      "\u001b[K     |████████████████████████████████| 190 kB 4.3 MB/s \n",
      "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from mmcv-full==1.4.6) (1.21.5)\n",
      "Requirement already satisfied: packaging in /usr/local/lib/python3.7/dist-packages (from mmcv-full==1.4.6) (21.3)\n",
      "Collecting addict\n",
      "  Downloading addict-2.4.0-py3-none-any.whl (3.8 kB)\n",
      "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging->mmcv-full==1.4.6) (3.0.7)\n",
      "Installing collected packages: yapf, addict, mmcv-full\n",
      "Successfully installed addict-2.4.0 mmcv-full-1.4.6 yapf-0.32.0\n",
      "\u001b[32mSuccessfully installed mmcv-full.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "# Install mmcv-full dependency via openmim\n",
    "!pip install openmim\n",
    "!mim install mmcv-full"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cloning into 'mmediting'...\n",
      "remote: Enumerating objects: 10110, done.\u001b[K\n",
      "remote: Counting objects: 100% (783/783), done.\u001b[K\n",
      "remote: Compressing objects: 100% (486/486), done.\u001b[K\n",
      "remote: Total 10110 (delta 365), reused 566 (delta 277), pack-reused 9327\u001b[K\n",
      "Receiving objects: 100% (10110/10110), 6.05 MiB | 12.56 MiB/s, done.\n",
      "Resolving deltas: 100% (6710/6710), done.\n",
      "/content/mmediting\n",
      "Obtaining file:///content/mmediting\n",
      "Requirement already satisfied: lmdb in /usr/local/lib/python3.7/dist-packages (from mmedit==0.13.0) (0.99)\n",
      "Requirement already satisfied: mmcv-full>=1.3.1 in /usr/local/lib/python3.7/dist-packages (from mmedit==0.13.0) (1.4.6)\n",
      "Requirement already satisfied: opencv-python<=4.5.4.60 in /usr/local/lib/python3.7/dist-packages (from mmedit==0.13.0) (4.1.2.30)\n",
      "Requirement already satisfied: scikit-image in /usr/local/lib/python3.7/dist-packages (from mmedit==0.13.0) (0.18.3)\n",
      "Requirement already satisfied: tensorboard in /usr/local/lib/python3.7/dist-packages (from mmedit==0.13.0) (2.8.0)\n",
      "Requirement already satisfied: yapf in /usr/local/lib/python3.7/dist-packages (from mmedit==0.13.0) (0.32.0)\n",
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      "Requirement already satisfied: addict in /usr/local/lib/python3.7/dist-packages (from mmcv-full>=1.3.1->mmedit==0.13.0) (2.4.0)\n",
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      "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.7/dist-packages (from google-auth<3,>=1.6.3->tensorboard->mmedit==0.13.0) (4.8)\n",
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      "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.7/dist-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard->mmedit==0.13.0) (1.3.1)\n",
      "Requirement already satisfied: importlib-metadata>=4.4 in /usr/local/lib/python3.7/dist-packages (from markdown>=2.6.8->tensorboard->mmedit==0.13.0) (4.11.2)\n",
      "Requirement already satisfied: typing-extensions>=3.6.4 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata>=4.4->markdown>=2.6.8->tensorboard->mmedit==0.13.0) (3.10.0.2)\n",
      "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata>=4.4->markdown>=2.6.8->tensorboard->mmedit==0.13.0) (3.7.0)\n",
      "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /usr/local/lib/python3.7/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard->mmedit==0.13.0) (0.4.8)\n",
      "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tensorboard->mmedit==0.13.0) (1.24.3)\n",
      "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tensorboard->mmedit==0.13.0) (2.10)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tensorboard->mmedit==0.13.0) (2021.10.8)\n",
      "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tensorboard->mmedit==0.13.0) (3.0.4)\n",
      "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.7/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard->mmedit==0.13.0) (3.2.0)\n",
      "Installing collected packages: mmedit\n",
      "  Running setup.py develop for mmedit\n",
      "Successfully installed mmedit-0.13.0\n"
     ]
    }
   ],
   "source": [
    "# Install mmediting from source\n",
    "!git clone https://github.com/open-mmlab/mmediting.git\n",
    "%cd mmediting\n",
    "!pip install -e ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.13.0\n"
     ]
    }
   ],
   "source": [
    "# Check MMEditing installation\n",
    "import mmedit\n",
    "print(mmedit.__version__)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "a-3YqEpeF9R6"
   },
   "source": [
    "## Perform inference with a MMEditing mattor\n",
    "\n",
    "MMEditing already provides high level APIs to do inference and training."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------------------------------------------------------\n",
      "config id: indexnet_mobv2_1x16_78k_comp1k\n",
      "architecture                                  indexnet\n",
      "comp1k/conn                                   44.8\n",
      "comp1k/grad                                   25.5\n",
      "comp1k/mse                                    0.012\n",
      "comp1k/sad                                    45.6\n",
      "config                                        configs/mattors/indexnet/indexn...\n",
      "model                                         indexnet\n",
      "paper                                         https://arxiv.org/abs/1908.00672\n",
      "readme                                        configs/mattors/indexnet/README.md\n",
      "training_data                                 comp1k\n",
      "weight                                        https://download.openmmlab.com/...\n",
      "--------------------------------------------------------------------------------\n",
      "config id: indexnet_dimaug_mobv2_1x16_78k_comp1k\n",
      "architecture                                  indexnet\n",
      "comp1k/conn                                   49.5\n",
      "comp1k/grad                                   30.8\n",
      "comp1k/mse                                    0.016\n",
      "comp1k/sad                                    50.1\n",
      "config                                        configs/mattors/indexnet/indexn...\n",
      "model                                         indexnet\n",
      "paper                                         https://arxiv.org/abs/1908.00672\n",
      "readme                                        configs/mattors/indexnet/README.md\n",
      "training_data                                 comp1k\n",
      "weight                                        https://download.openmmlab.com/...\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# List all available IndexNet models\n",
    "!mim search mmedit --model indexnet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "processing indexnet_mobv2_1x16_78k_comp1k...\n",
      "\u001b[?25l  [####################################]  100%          \u001b[?25h\n",
      "\u001b[32mSuccessfully downloaded indexnet_mobv2_1x16_78k_comp1k_SAD-45.6_20200618_173817-26dd258d.pth to /content/mmediting/checkpoints\u001b[0m\n",
      "\u001b[32mSuccessfully dumped indexnet_mobv2_1x16_78k_comp1k.py to /content/mmediting/checkpoints\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "# Download config and checkpoints for IndexNet to current working directory\n",
    "!mkdir -p checkpoints\n",
    "!mim download mmedit --config indexnet_mobv2_1x16_78k_comp1k --dest checkpoints"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "load checkpoint from local path: checkpoints/indexnet_mobv2_1x16_78k_comp1k_SAD-45.6_20200618_173817-26dd258d.pth\n"
     ]
    }
   ],
   "source": [
    "from mmedit.apis import matting_inference, init_model\n",
    "\n",
    "# Choose to use a config and initialize the mattor\n",
    "config = 'configs/mattors/indexnet/indexnet_mobv2_1x16_78k_comp1k.py'\n",
    "# Setup a checkpoint file to load\n",
    "checkpoint = 'checkpoints/indexnet_mobv2_1x16_78k_comp1k_SAD-45.6_20200618_173817-26dd258d.pth'\n",
    "# Initialize the recognizer\n",
    "model = init_model(config, checkpoint, device='cuda:0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f42b2d51c90>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x640 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import mmcv\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "# Sample images path\n",
    "merged_path = './tests/data/merged/GT05.jpg'\n",
    "trimap_path = './tests/data/trimap/GT05.png'\n",
    "\n",
    "# Plot sample images\n",
    "merged = mmcv.imread(merged_path)\n",
    "trimap = mmcv.imread(trimap_path)\n",
    "f, axarr = plt.subplots(1, 2)\n",
    "f.dpi = 160\n",
    "axarr[0].axis('off')\n",
    "axarr[0].imshow(mmcv.bgr2rgb(merged))\n",
    "axarr[1].axis('off')\n",
    "axarr[1].imshow(trimap)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use the mattor to do inference\n",
    "pred_alpha = matting_inference(model, merged_path, trimap_path) * 255"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 480x320 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot result\n",
    "plt.gcf().dpi = 80\n",
    "plt.axis('off')\n",
    "plt.imshow(pred_alpha, cmap=plt.get_cmap('gray'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "o2s8h_rqRX-3"
   },
   "source": [
    "## Train a mattor on a customized dataset\n",
    "\n",
    "To train a new mattor, there are usually three things to do:\n",
    "\n",
    "1. Support a new dataset\n",
    "2. Modify the config\n",
    "3. Train a new mattor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Gxs3HR86RatF"
   },
   "source": [
    "### Support a new dataset\n",
    "\n",
    "In this tutorial, we gives an example to convert the data into the format of existing datasets. \n",
    "\n",
    "<!-- TODO: Other methods and more advanced usages can be found in the [doc](TODO). -->\n",
    "\n",
    "Firstly, let's download the only available open source matting dataset from [alphamatting.com](http://alphamatting.com/). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
      "100 17.3M  100 17.3M    0     0  4241k      0  0:00:04  0:00:04 --:--:-- 4242k\n",
      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
      "100  366k  100  366k    0     0   221k      0  0:00:01  0:00:01 --:--:--  221k\n",
      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
      "100 2215k  100 2215k    0     0   814k      0  0:00:02  0:00:02 --:--:--  813k\n",
      "Archive:  data/alphamatting/input_training_lowres.zip\n",
      "  inflating: data/alphamatting/merged/GT27.png  \n",
      "  inflating: data/alphamatting/merged/GT01.png  \n",
      "  inflating: data/alphamatting/merged/GT02.png  \n",
      "  inflating: data/alphamatting/merged/GT03.png  \n",
      "  inflating: data/alphamatting/merged/GT04.png  \n",
      "  inflating: data/alphamatting/merged/GT05.png  \n",
      "  inflating: data/alphamatting/merged/GT06.png  \n",
      "  inflating: data/alphamatting/merged/GT07.png  \n",
      "  inflating: data/alphamatting/merged/GT08.png  \n",
      "  inflating: data/alphamatting/merged/GT09.png  \n",
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      "Archive:  data/alphamatting/trimap_training_lowres.zip\n",
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      "Archive:  data/alphamatting/gt_training_lowres.zip\n",
      "  inflating: data/alphamatting/alpha/GT27.png  \n",
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      "  inflating: data/alphamatting/alpha/GT22.png  \n",
      "  inflating: data/alphamatting/alpha/GT23.png  \n",
      "  inflating: data/alphamatting/alpha/GT24.png  \n",
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      "  inflating: data/alphamatting/alpha/GT26.png  \n"
     ]
    }
   ],
   "source": [
    "!mkdir -p data/alphamatting/\n",
    "!curl http://alphamatting.com/datasets/zip/input_training_lowres.zip -o data/alphamatting/input_training_lowres.zip\n",
    "!curl http://alphamatting.com/datasets/zip/trimap_training_lowres.zip -o data/alphamatting/trimap_training_lowres.zip\n",
    "!curl http://alphamatting.com/datasets/zip/gt_training_lowres.zip -o data/alphamatting/gt_training_lowres.zip\n",
    "!unzip -o data/alphamatting/input_training_lowres.zip -d data/alphamatting/merged\n",
    "!unzip -o data/alphamatting/trimap_training_lowres.zip -d data/alphamatting/trimap\n",
    "!unzip -o data/alphamatting/gt_training_lowres.zip -d data/alphamatting/alpha"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "DkmZzafQWrLP"
   },
   "source": [
    "Then we create the annotation file for training data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_file = 27\n",
    "num_training = 20  # use 20 samples for training, 7 for test\n",
    "\n",
    "training_ann = list()\n",
    "for i in range(num_training):\n",
    "  ann = dict()\n",
    "  ann['merged_path'] = f'merged/GT{i+1:02d}.png'\n",
    "  ann['alpha_path'] = f'alpha/GT{i+1:02d}.png'\n",
    "  # since data from alphamatting.com is not composited, we use original image \n",
    "  # as fg and bg\n",
    "  ann['fg_path'] = ann['merged_path']\n",
    "  ann['bg_path'] = ann['merged_path']\n",
    "  training_ann.append(ann)\n",
    "\n",
    "import mmcv\n",
    "mmcv.dump(training_ann, './data/alphamatting/training_list.json')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MKWmqxkdZA51"
   },
   "source": [
    "Let's create the annotation file for test data in the same way."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_trimap = 1\n",
    "test_ann = list()\n",
    "for i in range(num_training, num_file):\n",
    "  for j in range(num_trimap):\n",
    "    ann = dict()\n",
    "    ann['merged_path'] = f'merged/GT{i+1:02d}.png'\n",
    "    ann['trimap_path'] = f'trimap/Trimap{j+1}/GT{i+1:02d}.png'\n",
    "    ann['alpha_path'] = f'alpha/GT{i+1:02d}.png'\n",
    "    test_ann.append(ann)\n",
    "\n",
    "mmcv.dump(test_ann, './data/alphamatting/test_list.json')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "URUDy9x8cs-U"
   },
   "source": [
    "### Modify the config\n",
    "\n",
    "In the next step, we need to modify the config for the training. To accelerate the process, we finetune a mattor using a pre-trained mattor."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "model = dict(\n",
      "    type='IndexNet',\n",
      "    backbone=dict(\n",
      "        type='SimpleEncoderDecoder',\n",
      "        encoder=dict(type='IndexNetEncoder', in_channels=4, freeze_bn=True),\n",
      "        decoder=dict(type='IndexNetDecoder')),\n",
      "    loss_alpha=dict(type='CharbonnierLoss', loss_weight=0.5, sample_wise=True),\n",
      "    loss_comp=dict(\n",
      "        type='CharbonnierCompLoss', loss_weight=1.5, sample_wise=True),\n",
      "    pretrained='open-mmlab://mmedit/mobilenet_v2')\n",
      "train_cfg = dict(train_backbone=True)\n",
      "test_cfg = dict(metrics=['SAD', 'MSE', 'GRAD', 'CONN'])\n",
      "dataset_type = 'AdobeComp1kDataset'\n",
      "data_root = 'data/adobe_composition-1k'\n",
      "img_norm_cfg = dict(\n",
      "    mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225], to_rgb=True)\n",
      "train_pipeline = [\n",
      "    dict(type='LoadImageFromFile', key='alpha', flag='grayscale'),\n",
      "    dict(type='LoadImageFromFile', key='fg'),\n",
      "    dict(type='LoadImageFromFile', key='bg'),\n",
      "    dict(type='LoadImageFromFile', key='merged', save_original_img=True),\n",
      "    dict(type='GenerateTrimapWithDistTransform', dist_thr=20),\n",
      "    dict(\n",
      "        type='CropAroundUnknown',\n",
      "        keys=['alpha', 'merged', 'ori_merged', 'fg', 'bg', 'trimap'],\n",
      "        crop_sizes=[320, 480, 640],\n",
      "        interpolations=[\n",
      "            'bicubic', 'bicubic', 'bicubic', 'bicubic', 'bicubic', 'nearest'\n",
      "        ]),\n",
      "    dict(\n",
      "        type='Resize',\n",
      "        keys=['trimap'],\n",
      "        scale=(320, 320),\n",
      "        keep_ratio=False,\n",
      "        interpolation='nearest'),\n",
      "    dict(\n",
      "        type='Resize',\n",
      "        keys=['alpha', 'merged', 'ori_merged', 'fg', 'bg'],\n",
      "        scale=(320, 320),\n",
      "        keep_ratio=False,\n",
      "        interpolation='bicubic'),\n",
      "    dict(\n",
      "        type='Flip',\n",
      "        keys=['alpha', 'merged', 'ori_merged', 'fg', 'bg', 'trimap']),\n",
      "    dict(\n",
      "        type='RescaleToZeroOne',\n",
      "        keys=['merged', 'alpha', 'ori_merged', 'fg', 'bg', 'trimap']),\n",
      "    dict(\n",
      "        type='Normalize',\n",
      "        keys=['merged'],\n",
      "        mean=[0.485, 0.456, 0.406],\n",
      "        std=[0.229, 0.224, 0.225],\n",
      "        to_rgb=True),\n",
      "    dict(\n",
      "        type='Collect',\n",
      "        keys=['merged', 'alpha', 'trimap', 'ori_merged', 'fg', 'bg'],\n",
      "        meta_keys=[]),\n",
      "    dict(\n",
      "        type='ImageToTensor',\n",
      "        keys=['merged', 'alpha', 'trimap', 'ori_merged', 'fg', 'bg'])\n",
      "]\n",
      "test_pipeline = [\n",
      "    dict(\n",
      "        type='LoadImageFromFile',\n",
      "        key='alpha',\n",
      "        flag='grayscale',\n",
      "        save_original_img=True),\n",
      "    dict(\n",
      "        type='LoadImageFromFile',\n",
      "        key='trimap',\n",
      "        flag='grayscale',\n",
      "        save_original_img=True),\n",
      "    dict(type='LoadImageFromFile', key='merged'),\n",
      "    dict(type='RescaleToZeroOne', keys=['merged', 'trimap']),\n",
      "    dict(\n",
      "        type='Normalize',\n",
      "        keys=['merged'],\n",
      "        mean=[0.485, 0.456, 0.406],\n",
      "        std=[0.229, 0.224, 0.225],\n",
      "        to_rgb=True),\n",
      "    dict(\n",
      "        type='Resize',\n",
      "        keys=['trimap'],\n",
      "        size_factor=32,\n",
      "        interpolation='nearest'),\n",
      "    dict(\n",
      "        type='Resize',\n",
      "        keys=['merged'],\n",
      "        size_factor=32,\n",
      "        interpolation='bicubic'),\n",
      "    dict(\n",
      "        type='Collect',\n",
      "        keys=['merged', 'trimap'],\n",
      "        meta_keys=[\n",
      "            'merged_path', 'interpolation', 'merged_ori_shape', 'ori_alpha',\n",
      "            'ori_trimap'\n",
      "        ]),\n",
      "    dict(type='ImageToTensor', keys=['merged', 'trimap'])\n",
      "]\n",
      "data = dict(\n",
      "    workers_per_gpu=8,\n",
      "    train_dataloader=dict(samples_per_gpu=16, drop_last=True),\n",
      "    val_dataloader=dict(samples_per_gpu=1),\n",
      "    test_dataloader=dict(samples_per_gpu=1),\n",
      "    train=dict(\n",
      "        type='AdobeComp1kDataset',\n",
      "        ann_file='data/adobe_composition-1k/training_list.json',\n",
      "        data_prefix='data/adobe_composition-1k',\n",
      "        pipeline=[\n",
      "            dict(type='LoadImageFromFile', key='alpha', flag='grayscale'),\n",
      "            dict(type='LoadImageFromFile', key='fg'),\n",
      "            dict(type='LoadImageFromFile', key='bg'),\n",
      "            dict(\n",
      "                type='LoadImageFromFile', key='merged',\n",
      "                save_original_img=True),\n",
      "            dict(type='GenerateTrimapWithDistTransform', dist_thr=20),\n",
      "            dict(\n",
      "                type='CropAroundUnknown',\n",
      "                keys=['alpha', 'merged', 'ori_merged', 'fg', 'bg', 'trimap'],\n",
      "                crop_sizes=[320, 480, 640],\n",
      "                interpolations=[\n",
      "                    'bicubic', 'bicubic', 'bicubic', 'bicubic', 'bicubic',\n",
      "                    'nearest'\n",
      "                ]),\n",
      "            dict(\n",
      "                type='Resize',\n",
      "                keys=['trimap'],\n",
      "                scale=(320, 320),\n",
      "                keep_ratio=False,\n",
      "                interpolation='nearest'),\n",
      "            dict(\n",
      "                type='Resize',\n",
      "                keys=['alpha', 'merged', 'ori_merged', 'fg', 'bg'],\n",
      "                scale=(320, 320),\n",
      "                keep_ratio=False,\n",
      "                interpolation='bicubic'),\n",
      "            dict(\n",
      "                type='Flip',\n",
      "                keys=['alpha', 'merged', 'ori_merged', 'fg', 'bg', 'trimap']),\n",
      "            dict(\n",
      "                type='RescaleToZeroOne',\n",
      "                keys=['merged', 'alpha', 'ori_merged', 'fg', 'bg', 'trimap']),\n",
      "            dict(\n",
      "                type='Normalize',\n",
      "                keys=['merged'],\n",
      "                mean=[0.485, 0.456, 0.406],\n",
      "                std=[0.229, 0.224, 0.225],\n",
      "                to_rgb=True),\n",
      "            dict(\n",
      "                type='Collect',\n",
      "                keys=['merged', 'alpha', 'trimap', 'ori_merged', 'fg', 'bg'],\n",
      "                meta_keys=[]),\n",
      "            dict(\n",
      "                type='ImageToTensor',\n",
      "                keys=['merged', 'alpha', 'trimap', 'ori_merged', 'fg', 'bg'])\n",
      "        ]),\n",
      "    val=dict(\n",
      "        type='AdobeComp1kDataset',\n",
      "        ann_file='data/adobe_composition-1k/test_list.json',\n",
      "        data_prefix='data/adobe_composition-1k',\n",
      "        pipeline=[\n",
      "            dict(\n",
      "                type='LoadImageFromFile',\n",
      "                key='alpha',\n",
      "                flag='grayscale',\n",
      "                save_original_img=True),\n",
      "            dict(\n",
      "                type='LoadImageFromFile',\n",
      "                key='trimap',\n",
      "                flag='grayscale',\n",
      "                save_original_img=True),\n",
      "            dict(type='LoadImageFromFile', key='merged'),\n",
      "            dict(type='RescaleToZeroOne', keys=['merged', 'trimap']),\n",
      "            dict(\n",
      "                type='Normalize',\n",
      "                keys=['merged'],\n",
      "                mean=[0.485, 0.456, 0.406],\n",
      "                std=[0.229, 0.224, 0.225],\n",
      "                to_rgb=True),\n",
      "            dict(\n",
      "                type='Resize',\n",
      "                keys=['trimap'],\n",
      "                size_factor=32,\n",
      "                interpolation='nearest'),\n",
      "            dict(\n",
      "                type='Resize',\n",
      "                keys=['merged'],\n",
      "                size_factor=32,\n",
      "                interpolation='bicubic'),\n",
      "            dict(\n",
      "                type='Collect',\n",
      "                keys=['merged', 'trimap'],\n",
      "                meta_keys=[\n",
      "                    'merged_path', 'interpolation', 'merged_ori_shape',\n",
      "                    'ori_alpha', 'ori_trimap'\n",
      "                ]),\n",
      "            dict(type='ImageToTensor', keys=['merged', 'trimap'])\n",
      "        ]),\n",
      "    test=dict(\n",
      "        type='AdobeComp1kDataset',\n",
      "        ann_file='data/adobe_composition-1k/test_list.json',\n",
      "        data_prefix='data/adobe_composition-1k',\n",
      "        pipeline=[\n",
      "            dict(\n",
      "                type='LoadImageFromFile',\n",
      "                key='alpha',\n",
      "                flag='grayscale',\n",
      "                save_original_img=True),\n",
      "            dict(\n",
      "                type='LoadImageFromFile',\n",
      "                key='trimap',\n",
      "                flag='grayscale',\n",
      "                save_original_img=True),\n",
      "            dict(type='LoadImageFromFile', key='merged'),\n",
      "            dict(type='RescaleToZeroOne', keys=['merged', 'trimap']),\n",
      "            dict(\n",
      "                type='Normalize',\n",
      "                keys=['merged'],\n",
      "                mean=[0.485, 0.456, 0.406],\n",
      "                std=[0.229, 0.224, 0.225],\n",
      "                to_rgb=True),\n",
      "            dict(\n",
      "                type='Resize',\n",
      "                keys=['trimap'],\n",
      "                size_factor=32,\n",
      "                interpolation='nearest'),\n",
      "            dict(\n",
      "                type='Resize',\n",
      "                keys=['merged'],\n",
      "                size_factor=32,\n",
      "                interpolation='bicubic'),\n",
      "            dict(\n",
      "                type='Collect',\n",
      "                keys=['merged', 'trimap'],\n",
      "                meta_keys=[\n",
      "                    'merged_path', 'interpolation', 'merged_ori_shape',\n",
      "                    'ori_alpha', 'ori_trimap'\n",
      "                ]),\n",
      "            dict(type='ImageToTensor', keys=['merged', 'trimap'])\n",
      "        ]))\n",
      "optimizers = dict(\n",
      "    constructor='DefaultOptimizerConstructor',\n",
      "    type='Adam',\n",
      "    lr=0.01,\n",
      "    paramwise_cfg=dict(\n",
      "        custom_keys=dict({'encoder.layers': dict(lr_mult=0.01)})))\n",
      "lr_config = dict(policy='Step', step=[52000, 67600], gamma=0.1, by_epoch=False)\n",
      "checkpoint_config = dict(interval=2600, by_epoch=False)\n",
      "evaluation = dict(interval=2600, save_image=False)\n",
      "log_config = dict(\n",
      "    interval=10, hooks=[dict(type='TextLoggerHook', by_epoch=False)])\n",
      "total_iters = 78000\n",
      "dist_params = dict(backend='nccl')\n",
      "log_level = 'INFO'\n",
      "work_dir = './work_dirs/indexnet'\n",
      "load_from = None\n",
      "resume_from = None\n",
      "workflow = [('train', 1)]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from mmcv import Config\n",
    "cfg = Config.fromfile('./configs/mattors/indexnet/indexnet_mobv2_1x16_78k_comp1k.py')\n",
    "print(cfg.pretty_text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "P04K_cv-dIew"
   },
   "source": [
    "Given a config that trains a IndexNet model on Adobe Composition-1k dataset, we need to modify some values to use it for training IndexNet on the dataset we just created."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "model = dict(\n",
      "    type='IndexNet',\n",
      "    backbone=dict(\n",
      "        type='SimpleEncoderDecoder',\n",
      "        encoder=dict(type='IndexNetEncoder', in_channels=4, freeze_bn=True),\n",
      "        decoder=dict(type='IndexNetDecoder')),\n",
      "    loss_alpha=dict(type='CharbonnierLoss', loss_weight=0.5, sample_wise=True),\n",
      "    loss_comp=dict(\n",
      "        type='CharbonnierCompLoss', loss_weight=1.5, sample_wise=True),\n",
      "    pretrained=None)\n",
      "train_cfg = dict(train_backbone=True)\n",
      "test_cfg = dict(metrics=['SAD', 'MSE', 'GRAD', 'CONN'])\n",
      "dataset_type = 'AdobeComp1kDataset'\n",
      "data_root = 'data/adobe_composition-1k'\n",
      "img_norm_cfg = dict(\n",
      "    mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225], to_rgb=True)\n",
      "train_pipeline = [\n",
      "    dict(type='LoadImageFromFile', key='alpha', flag='grayscale'),\n",
      "    dict(type='LoadImageFromFile', key='fg'),\n",
      "    dict(type='LoadImageFromFile', key='bg'),\n",
      "    dict(type='LoadImageFromFile', key='merged', save_original_img=True),\n",
      "    dict(type='GenerateTrimapWithDistTransform', dist_thr=20),\n",
      "    dict(\n",
      "        type='CropAroundUnknown',\n",
      "        keys=['alpha', 'merged', 'ori_merged', 'fg', 'bg', 'trimap'],\n",
      "        crop_sizes=[320, 480, 640],\n",
      "        interpolations=[\n",
      "            'bicubic', 'bicubic', 'bicubic', 'bicubic', 'bicubic', 'nearest'\n",
      "        ]),\n",
      "    dict(\n",
      "        type='Resize',\n",
      "        keys=['trimap'],\n",
      "        scale=(320, 320),\n",
      "        keep_ratio=False,\n",
      "        interpolation='nearest'),\n",
      "    dict(\n",
      "        type='Resize',\n",
      "        keys=['alpha', 'merged', 'ori_merged', 'fg', 'bg'],\n",
      "        scale=(320, 320),\n",
      "        keep_ratio=False,\n",
      "        interpolation='bicubic'),\n",
      "    dict(\n",
      "        type='Flip',\n",
      "        keys=['alpha', 'merged', 'ori_merged', 'fg', 'bg', 'trimap']),\n",
      "    dict(\n",
      "        type='RescaleToZeroOne',\n",
      "        keys=['merged', 'alpha', 'ori_merged', 'fg', 'bg', 'trimap']),\n",
      "    dict(\n",
      "        type='Normalize',\n",
      "        keys=['merged'],\n",
      "        mean=[0.485, 0.456, 0.406],\n",
      "        std=[0.229, 0.224, 0.225],\n",
      "        to_rgb=True),\n",
      "    dict(\n",
      "        type='Collect',\n",
      "        keys=['merged', 'alpha', 'trimap', 'ori_merged', 'fg', 'bg'],\n",
      "        meta_keys=[]),\n",
      "    dict(\n",
      "        type='ImageToTensor',\n",
      "        keys=['merged', 'alpha', 'trimap', 'ori_merged', 'fg', 'bg'])\n",
      "]\n",
      "test_pipeline = [\n",
      "    dict(\n",
      "        type='LoadImageFromFile',\n",
      "        key='alpha',\n",
      "        flag='grayscale',\n",
      "        save_original_img=True),\n",
      "    dict(\n",
      "        type='LoadImageFromFile',\n",
      "        key='trimap',\n",
      "        flag='grayscale',\n",
      "        save_original_img=True),\n",
      "    dict(type='LoadImageFromFile', key='merged'),\n",
      "    dict(type='RescaleToZeroOne', keys=['merged', 'trimap']),\n",
      "    dict(\n",
      "        type='Normalize',\n",
      "        keys=['merged'],\n",
      "        mean=[0.485, 0.456, 0.406],\n",
      "        std=[0.229, 0.224, 0.225],\n",
      "        to_rgb=True),\n",
      "    dict(\n",
      "        type='Resize',\n",
      "        keys=['trimap'],\n",
      "        size_factor=32,\n",
      "        interpolation='nearest'),\n",
      "    dict(\n",
      "        type='Resize',\n",
      "        keys=['merged'],\n",
      "        size_factor=32,\n",
      "        interpolation='bicubic'),\n",
      "    dict(\n",
      "        type='Collect',\n",
      "        keys=['merged', 'trimap'],\n",
      "        meta_keys=[\n",
      "            'merged_path', 'interpolation', 'merged_ori_shape', 'ori_alpha',\n",
      "            'ori_trimap'\n",
      "        ]),\n",
      "    dict(type='ImageToTensor', keys=['merged', 'trimap'])\n",
      "]\n",
      "data = dict(\n",
      "    workers_per_gpu=1,\n",
      "    train_dataloader=dict(samples_per_gpu=12, drop_last=True),\n",
      "    val_dataloader=dict(samples_per_gpu=1),\n",
      "    test_dataloader=dict(samples_per_gpu=1),\n",
      "    train=dict(\n",
      "        type='AdobeComp1kDataset',\n",
      "        ann_file='./data/alphamatting/training_list.json',\n",
      "        data_prefix='./data/alphamatting/',\n",
      "        pipeline=[\n",
      "            dict(type='LoadImageFromFile', key='alpha', flag='grayscale'),\n",
      "            dict(type='LoadImageFromFile', key='fg'),\n",
      "            dict(type='LoadImageFromFile', key='bg'),\n",
      "            dict(\n",
      "                type='LoadImageFromFile', key='merged',\n",
      "                save_original_img=True),\n",
      "            dict(type='GenerateTrimapWithDistTransform', dist_thr=20),\n",
      "            dict(\n",
      "                type='CropAroundUnknown',\n",
      "                keys=['alpha', 'merged', 'ori_merged', 'fg', 'bg', 'trimap'],\n",
      "                crop_sizes=[320, 480, 640],\n",
      "                interpolations=[\n",
      "                    'bicubic', 'bicubic', 'bicubic', 'bicubic', 'bicubic',\n",
      "                    'nearest'\n",
      "                ]),\n",
      "            dict(\n",
      "                type='Resize',\n",
      "                keys=['trimap'],\n",
      "                scale=(320, 320),\n",
      "                keep_ratio=False,\n",
      "                interpolation='nearest'),\n",
      "            dict(\n",
      "                type='Resize',\n",
      "                keys=['alpha', 'merged', 'ori_merged', 'fg', 'bg'],\n",
      "                scale=(320, 320),\n",
      "                keep_ratio=False,\n",
      "                interpolation='bicubic'),\n",
      "            dict(\n",
      "                type='Flip',\n",
      "                keys=['alpha', 'merged', 'ori_merged', 'fg', 'bg', 'trimap']),\n",
      "            dict(\n",
      "                type='RescaleToZeroOne',\n",
      "                keys=['merged', 'alpha', 'ori_merged', 'fg', 'bg', 'trimap']),\n",
      "            dict(\n",
      "                type='Normalize',\n",
      "                keys=['merged'],\n",
      "                mean=[0.485, 0.456, 0.406],\n",
      "                std=[0.229, 0.224, 0.225],\n",
      "                to_rgb=True),\n",
      "            dict(\n",
      "                type='Collect',\n",
      "                keys=['merged', 'alpha', 'trimap', 'ori_merged', 'fg', 'bg'],\n",
      "                meta_keys=[]),\n",
      "            dict(\n",
      "                type='ImageToTensor',\n",
      "                keys=['merged', 'alpha', 'trimap', 'ori_merged', 'fg', 'bg'])\n",
      "        ]),\n",
      "    val=dict(\n",
      "        type='AdobeComp1kDataset',\n",
      "        ann_file='./data/alphamatting/test_list.json',\n",
      "        data_prefix='./data/alphamatting/',\n",
      "        pipeline=[\n",
      "            dict(\n",
      "                type='LoadImageFromFile',\n",
      "                key='alpha',\n",
      "                flag='grayscale',\n",
      "                save_original_img=True),\n",
      "            dict(\n",
      "                type='LoadImageFromFile',\n",
      "                key='trimap',\n",
      "                flag='grayscale',\n",
      "                save_original_img=True),\n",
      "            dict(type='LoadImageFromFile', key='merged'),\n",
      "            dict(type='RescaleToZeroOne', keys=['merged', 'trimap']),\n",
      "            dict(\n",
      "                type='Normalize',\n",
      "                keys=['merged'],\n",
      "                mean=[0.485, 0.456, 0.406],\n",
      "                std=[0.229, 0.224, 0.225],\n",
      "                to_rgb=True),\n",
      "            dict(\n",
      "                type='Resize',\n",
      "                keys=['trimap'],\n",
      "                size_factor=32,\n",
      "                interpolation='nearest'),\n",
      "            dict(\n",
      "                type='Resize',\n",
      "                keys=['merged'],\n",
      "                size_factor=32,\n",
      "                interpolation='bicubic'),\n",
      "            dict(\n",
      "                type='Collect',\n",
      "                keys=['merged', 'trimap'],\n",
      "                meta_keys=[\n",
      "                    'merged_path', 'interpolation', 'merged_ori_shape',\n",
      "                    'ori_alpha', 'ori_trimap'\n",
      "                ]),\n",
      "            dict(type='ImageToTensor', keys=['merged', 'trimap'])\n",
      "        ]),\n",
      "    test=dict(\n",
      "        type='AdobeComp1kDataset',\n",
      "        ann_file='./data/alphamatting/test_list.json',\n",
      "        data_prefix='./data/alphamatting/',\n",
      "        pipeline=[\n",
      "            dict(\n",
      "                type='LoadImageFromFile',\n",
      "                key='alpha',\n",
      "                flag='grayscale',\n",
      "                save_original_img=True),\n",
      "            dict(\n",
      "                type='LoadImageFromFile',\n",
      "                key='trimap',\n",
      "                flag='grayscale',\n",
      "                save_original_img=True),\n",
      "            dict(type='LoadImageFromFile', key='merged'),\n",
      "            dict(type='RescaleToZeroOne', keys=['merged', 'trimap']),\n",
      "            dict(\n",
      "                type='Normalize',\n",
      "                keys=['merged'],\n",
      "                mean=[0.485, 0.456, 0.406],\n",
      "                std=[0.229, 0.224, 0.225],\n",
      "                to_rgb=True),\n",
      "            dict(\n",
      "                type='Resize',\n",
      "                keys=['trimap'],\n",
      "                size_factor=32,\n",
      "                interpolation='nearest'),\n",
      "            dict(\n",
      "                type='Resize',\n",
      "                keys=['merged'],\n",
      "                size_factor=32,\n",
      "                interpolation='bicubic'),\n",
      "            dict(\n",
      "                type='Collect',\n",
      "                keys=['merged', 'trimap'],\n",
      "                meta_keys=[\n",
      "                    'merged_path', 'interpolation', 'merged_ori_shape',\n",
      "                    'ori_alpha', 'ori_trimap'\n",
      "                ]),\n",
      "            dict(type='ImageToTensor', keys=['merged', 'trimap'])\n",
      "        ]))\n",
      "optimizers = dict(\n",
      "    constructor='DefaultOptimizerConstructor',\n",
      "    type='Adam',\n",
      "    lr=0.0025,\n",
      "    paramwise_cfg=dict(\n",
      "        custom_keys=dict({'encoder.layers': dict(lr_mult=0.01)})))\n",
      "lr_config = None\n",
      "checkpoint_config = dict(interval=40, by_epoch=False)\n",
      "evaluation = dict(interval=20, save_image=False)\n",
      "log_config = dict(\n",
      "    interval=5, hooks=[dict(type='TextLoggerHook', by_epoch=False)])\n",
      "total_iters = 50\n",
      "dist_params = dict(backend='nccl')\n",
      "log_level = 'INFO'\n",
      "work_dir = './tutorial_exps/indexnet'\n",
      "load_from = './checkpoints/indexnet_mobv2_1x16_78k_comp1k_SAD-45.6_20200618_173817-26dd258d.pth'\n",
      "resume_from = None\n",
      "workflow = [('train', 1)]\n",
      "seed = 0\n",
      "gpus = 1\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from mmcv import Config\n",
    "cfg = Config.fromfile('./configs/mattors/indexnet/indexnet_mobv2_1x16_78k_comp1k.py')\n",
    "\n",
    "from mmcv.runner import set_random_seed\n",
    "\n",
    "# Modify dataset type and path\n",
    "cfg.data.train.type = 'AdobeComp1kDataset'\n",
    "cfg.data.train.ann_file = './data/alphamatting/training_list.json'\n",
    "cfg.data.train.data_prefix = './data/alphamatting/'\n",
    "\n",
    "cfg.data.val.type = 'AdobeComp1kDataset'\n",
    "cfg.data.val.ann_file = './data/alphamatting/test_list.json'\n",
    "cfg.data.val.data_prefix = './data/alphamatting/'\n",
    "\n",
    "cfg.data.test.type = 'AdobeComp1kDataset'\n",
    "cfg.data.test.ann_file = './data/alphamatting/test_list.json'\n",
    "cfg.data.test.data_prefix = './data/alphamatting/'\n",
    "\n",
    "# We can use the pre-trained IndexNet model\n",
    "cfg.model.pretrained = None\n",
    "cfg.load_from = './checkpoints/indexnet_mobv2_1x16_78k_comp1k_SAD-45.6_20200618_173817-26dd258d.pth'\n",
    "\n",
    "# Set up working dir to save files and logs.\n",
    "cfg.work_dir = './tutorial_exps/indexnet'\n",
    "\n",
    "# Use smaller batch size for training\n",
    "cfg.data.train_dataloader.samples_per_gpu = 4\n",
    "cfg.data.workers_per_gpu = 1\n",
    "\n",
    "# The original learning rate (LR) is set for batch size 16 with 1 GPU.\n",
    "# We reduce the lr by a factor of 4 since we reduce the batch size.\n",
    "cfg.optimizers.lr = cfg.optimizers.lr / 4\n",
    "cfg.total_iters = 50\n",
    "cfg.lr_config = None\n",
    "\n",
    "# Evaluate every 20 iterations\n",
    "cfg.evaluation.interval = 20\n",
    "# We can set the checkpoint saving interval to reduce the storage cost\n",
    "cfg.checkpoint_config.interval = 40\n",
    "# We can set the log print interval to reduce the the times of printing log\n",
    "cfg.log_config.interval = 5\n",
    "\n",
    "# Set seed thus the results are more reproducible\n",
    "cfg.seed = 0\n",
    "set_random_seed(0, deterministic=False)\n",
    "cfg.gpus = 1\n",
    "\n",
    "print(cfg.pretty_text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "cI3uX5RqhFQQ"
   },
   "source": [
    "### Train a new mattor\n",
    "\n",
    "Finally, lets initialize the dataset and mattor, then train a new mattor!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-03-19 18:04:51,382 - mmedit - INFO - load checkpoint from local path: ./checkpoints/indexnet_mobv2_1x16_78k_comp1k_SAD-45.6_20200618_173817-26dd258d.pth\n",
      "2022-03-19 18:04:51,502 - mmedit - INFO - Start running, host: root@df5395ef5373, work_dir: /content/mmediting/tutorial_exps/indexnet\n",
      "2022-03-19 18:04:51,504 - mmedit - INFO - Hooks will be executed in the following order:\n",
      "before_run:\n",
      "(NORMAL      ) CheckpointHook                     \n",
      "(VERY_LOW    ) TextLoggerHook                     \n",
      " -------------------- \n",
      "before_train_epoch:\n",
      "(LOW         ) IterTimerHook                      \n",
      "(VERY_LOW    ) TextLoggerHook                     \n",
      " -------------------- \n",
      "before_train_iter:\n",
      "(LOW         ) IterTimerHook                      \n",
      " -------------------- \n",
      "after_train_iter:\n",
      "(NORMAL      ) CheckpointHook                     \n",
      "(LOW         ) IterTimerHook                      \n",
      "(LOW         ) EvalIterHook                       \n",
      "(VERY_LOW    ) TextLoggerHook                     \n",
      " -------------------- \n",
      "after_train_epoch:\n",
      "(NORMAL      ) CheckpointHook                     \n",
      "(VERY_LOW    ) TextLoggerHook                     \n",
      " -------------------- \n",
      "before_val_epoch:\n",
      "(LOW         ) IterTimerHook                      \n",
      "(VERY_LOW    ) TextLoggerHook                     \n",
      " -------------------- \n",
      "before_val_iter:\n",
      "(LOW         ) IterTimerHook                      \n",
      " -------------------- \n",
      "after_val_iter:\n",
      "(LOW         ) IterTimerHook                      \n",
      " -------------------- \n",
      "after_val_epoch:\n",
      "(VERY_LOW    ) TextLoggerHook                     \n",
      " -------------------- \n",
      "after_run:\n",
      "(VERY_LOW    ) TextLoggerHook                     \n",
      " -------------------- \n",
      "2022-03-19 18:04:51,507 - mmedit - INFO - workflow: [('train', 1)], max: 50 iters\n",
      "2022-03-19 18:04:51,509 - mmedit - INFO - Checkpoints will be saved to /content/mmediting/tutorial_exps/indexnet by HardDiskBackend.\n",
      "2022-03-19 18:05:14,448 - mmedit - INFO - Iter [5/50]\tlr: 2.500e-05, eta: 0:03:25, time: 4.576, data_time: 2.703, memory: 9012, loss_alpha: 0.0236, loss_comp: 0.0000, loss: 0.0236\n",
      "2022-03-19 18:05:40,543 - mmedit - INFO - Iter [10/50]\tlr: 2.500e-05, eta: 0:03:15, time: 5.219, data_time: 3.349, memory: 9012, loss_alpha: 0.0208, loss_comp: 0.0000, loss: 0.0208\n",
      "2022-03-19 18:06:04,926 - mmedit - INFO - Iter [15/50]\tlr: 2.500e-05, eta: 0:02:51, time: 4.877, data_time: 3.027, memory: 9012, loss_alpha: 0.0202, loss_comp: 0.0000, loss: 0.0202\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 7/7, 2.2 task/s, elapsed: 3s, ETA:     0s"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-03-19 18:06:32,649 - mmedit - INFO - Iter(val) [20]\tSAD: 4.4941, MSE: 0.0152, GRAD: 7.4875, CONN: 4.0191\n",
      "2022-03-19 18:06:56,870 - mmedit - INFO - Iter [25/50]\tlr: 2.500e-05, eta: 0:01:40, time: 5.480, data_time: 3.634, memory: 9012, loss_alpha: 0.0168, loss_comp: 0.0000, loss: 0.0168\n",
      "2022-03-19 18:07:22,340 - mmedit - INFO - Iter [30/50]\tlr: 2.500e-05, eta: 0:01:24, time: 5.094, data_time: 3.225, memory: 9012, loss_alpha: 0.0177, loss_comp: 0.0000, loss: 0.0177\n",
      "2022-03-19 18:07:46,750 - mmedit - INFO - Iter [35/50]\tlr: 2.500e-05, eta: 0:01:04, time: 4.882, data_time: 3.032, memory: 9012, loss_alpha: 0.0163, loss_comp: 0.0000, loss: 0.0163\n",
      "2022-03-19 18:08:11,291 - mmedit - INFO - Saving checkpoint at 40 iterations\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 7/7, 2.2 task/s, elapsed: 3s, ETA:     0s"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-03-19 18:08:14,809 - mmedit - INFO - Iter(val) [40]\tSAD: 4.3920, MSE: 0.0152, GRAD: 7.3852, CONN: 4.0367\n",
      "2022-03-19 18:08:39,360 - mmedit - INFO - Iter [45/50]\tlr: 2.500e-05, eta: 0:00:19, time: 5.535, data_time: 3.683, memory: 9012, loss_alpha: 0.0167, loss_comp: 0.0000, loss: 0.0167\n",
      "2022-03-19 18:09:03,816 - mmedit - INFO - Saving checkpoint at 50 iterations\n",
      "2022-03-19 18:09:04,137 - mmedit - INFO - Iter [50/50]\tlr: 2.500e-05, eta: 0:00:00, time: 4.955, data_time: 3.046, memory: 9012, loss_alpha: 0.0141, loss_comp: 0.0000, loss: 0.0141\n"
     ]
    }
   ],
   "source": [
    "import os.path as osp\n",
    "\n",
    "from mmedit.datasets import build_dataset\n",
    "from mmedit.models import build_model\n",
    "from mmedit.apis import train_model\n",
    "\n",
    "import mmcv\n",
    "\n",
    "# Build the dataset\n",
    "datasets = [build_dataset(cfg.data.train)]\n",
    "\n",
    "# Build the mattor\n",
    "model = build_model(cfg.model, train_cfg=cfg.train_cfg, test_cfg=cfg.test_cfg)\n",
    "\n",
    "# Create work_dir\n",
    "mmcv.mkdir_or_exist(osp.abspath(cfg.work_dir))\n",
    "\n",
    "# train the model\n",
    "train_model(model, datasets, cfg, distributed=False, validate=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "JPRUWpQ1Dy8W"
   },
   "source": [
    "### Understand the log\n",
    "\n",
    "From the log, we can have a basic understanding the training process and know how well the mattor is trained.\n",
    "\n",
    "Firstly, the MobileNetV2 backbone pre-trained on ImageNet is loaded, this is a common practice since training from scratch is more costly. The log shows that all the weights of the MobileNetV2 backbone are loaded while some parts of the model are missing in the loaded weight. But no worries! These parts have a larger learning rate than the pretrained parts (You can print out `cfg.optimizers` to see the pretrained parts with name prefix `encoder.layers` have a `lr_mult=0.01`).\n",
    "\n",
    "Secondly, after training, the mattor is evaluated by the default evaluation. The results show that the mattor achieves lower and lower SAD along the training process,\n",
    "\n",
    "Not bad!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "R73szzAYL4cu"
   },
   "source": [
    "## Test the trained mattor\n",
    "\n",
    "After finetuning the recognizer, let's check the prediction results!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 7/7, 2.1 task/s, elapsed: 3s, ETA:     0s\n",
      "SAD: 4.4220\n",
      "MSE: 0.0150\n",
      "GRAD: 7.1011\n",
      "CONN: 4.0517\n"
     ]
    }
   ],
   "source": [
    "from mmedit.apis import single_gpu_test\n",
    "from mmedit.datasets import build_dataloader\n",
    "from mmcv.parallel import MMDataParallel\n",
    "\n",
    "# Build a test dataloader and model\n",
    "dataset = build_dataset(cfg.data.test, dict(test_mode=True))\n",
    "data_loader = build_dataloader(\n",
    "        dataset,\n",
    "        samples_per_gpu=1,\n",
    "        workers_per_gpu=cfg.data.workers_per_gpu,\n",
    "        dist=False,\n",
    "        shuffle=False)\n",
    "model = MMDataParallel(model, device_ids=[0])\n",
    "\n",
    "# Perform the test with single gpu. Saving result images by setting\n",
    "# save_image and save_path arguments. The two arguments will be passed\n",
    "# to model.forword_test() where images are saved.\n",
    "# See https://github.com/open-mmlab/mmediting/blob/8b5c0c5f49e60fd6ab0503031b62dee7832faf72/mmedit/models/mattors/indexnet.py#L72.\n",
    "outputs = single_gpu_test(model, data_loader, save_image=True, save_path='./tutorial_exps/indexnet/results')\n",
    "\n",
    "# Pop out some unnecessary arguments\n",
    "eval_config = cfg.evaluation\n",
    "eval_config.pop('interval')\n",
    "eval_config.pop('save_image', False)\n",
    "eval_config.pop('save_path', None)\n",
    "\n",
    "eval_res = dataset.evaluate(outputs, **eval_config)\n",
    "print()  # endline of progress bar\n",
    "for name, val in eval_res.items():\n",
    "    print(f'{name}: {val:.04f}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "GGhi85oLtyvj"
   },
   "source": [
    "The result is the same as the last validation! This is because we use the same data for test and validation. Next, let's take a look at the visual results of the test! The results are saved in the directory `tutorial_exps/indexnet/results` that we specified."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "GT21.png  GT22.png  GT23.png  GT24.png\tGT25.png  GT26.png  GT27.png\n"
     ]
    }
   ],
   "source": [
    "!ls tutorial_exps/indexnet/results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "G8FO7XljukjJ"
   },
   "source": [
    "Plot the sample `GT21`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x960 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Sample images path\n",
    "merged_path = './data/alphamatting/merged/GT21.png'\n",
    "trimap_path = './data/alphamatting/trimap/Trimap1/GT21.png'\n",
    "alpha_path = './tutorial_exps/indexnet/results/GT21.png'\n",
    "\n",
    "# Plot sample images\n",
    "merged = mmcv.imread(merged_path)\n",
    "trimap = mmcv.imread(trimap_path)\n",
    "alpha = mmcv.imread(alpha_path)\n",
    "f, axarr = plt.subplots(1, 3)\n",
    "f.dpi = 240\n",
    "axarr[0].axis('off')\n",
    "axarr[0].imshow(mmcv.bgr2rgb(merged))\n",
    "axarr[1].axis('off')\n",
    "axarr[1].imshow(trimap)\n",
    "axarr[2].axis('off')\n",
    "axarr[2].imshow(alpha)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "HmYZRxw6wefo"
   },
   "source": [
    "Congratulations! You've done the tutorial of using MMEditing for matting task. Go to [Getting Started page](https://github.com/open-mmlab/mmediting/blob/master/docs/en/getting_started.md) for more usage of MMEditing and start to train your own mattor!"
   ]
  }
 ],
 "metadata": {
  "language_info": {
   "name": "python"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
